The present invention relates to processes for producing cartographic data in three dimensions from n two-dimensional images of a scene, provided by n sensors having different points of view of the scene.
It has for a very long time been known to define the position in space of structures which are present in a scene and can be seen in two images taken under different viewing angles, using stereoscopic techniques. This process has been generalized to the case of n images, n being an integer greater than 2, these n images constituting a stereoscopic system having a plurality of baselines.
Processes which include the following steps are, in particular, known:
the n sensors are calibrated (by using 3D knowledge of their relative position with respect to the scene which is observed and/or pattern recognition processes, so as to provide parameters of n models F.sub.i (x,y,z), each defining the relationship between a point in the scene, with coordinates x,y,z, and the coordinates (p,q).sub.i of its projection into each of the n images, for i ranging from 1 to n; PA1 the n images are set in correspondence, so as to locate the coordinates of the projection in the images of the same point in three-dimensional space; PA1 3D reconstruction is performed, consisting in obtaining the coordinates x, y and z of the 3D point corresponding to each match between images, on the basis of knowledge of the models F.sub.i, and the matched image points. PA1 detection of obstacles and autonomous guidance of a mobile robot in a fixed scene, PA1 3D modelling of real sites, PA1 mapping, PA1 aerial reconnaissance, for obtaining a terrain profile, PA1 the modelling of optimum trajectories during the preparation of an air mission.
A process of this type is described in the article by Sing Bing Kang et al. "A Multibaseline Stereo System with Active Illumination and Real-time Image Acquisition", Proceedings IEEE Int. Conf. on Computer Vision, pages 88-93, June 1995. The process proposed in this article employs four cameras whose optical axes converge approximately at the same point. The image provided by one of the cameras is chosen as a reference. Given that the axes of the cameras are not parallel, the associated epipolar lines are not parallel to the image lines. In order to simplify recovery of the altitude from the stereoscopic images, that is to say 3D reconstruction, the images are subjected to rectification which converts each original pair of images into another pair such that the epipolar lines resulting therefrom are parallel, equal and coincident with image scanning lines. The correspondence method uses a variable .lambda., defined as the distance from the optical centre along the viewing axis passing through the optical centre of the reference camera and the point in question, in order to calculate the search zone for potential homologues in the images to be matched with the reference image. Use of this variable .lambda. inevitably leads to a model with non-linear transition between the images, which makes the calculations more complicated. The strategy taught by the article, consisting in assigning equal significance to each pair, is a source of error whenever points are masked in one or more of the images.
A detailed study of algorithms for merging a plurality of representations in order to recover 3D cartographic data from a plurality of 2D images of a scene is given in the thesis at the Universite de Paris Sud, Centre d'Orsay, May 1988 "Construction et Fusion de Representations Visuelles 3D: Applications a la Robotique Mobile" [Constructing and Merging 3D Visual Representations: Applications in Mobile Robotics] by N. Ayache.